3 papers
math.OC2025
Tight Constraint Prediction of Six-Degree-of-Freedom Transformer-based Powered Descent Guidance
Julia Briden, Trey Gurga, Breanna Johnson +2
This work introduces Transformer-based Successive Convexification (T-SCvx), an extension of Transformer-based Powered Descent Guidance (T-PDG), generalizable for efficient six-degr…
cs.RO2025
Diffusion Policies for Generative Modeling of Spacecraft Trajectories
Julia Briden, Breanna Johnson, Richard Linares +1
Machine learning has demonstrated remarkable promise for solving the trajectory generation problem and in paving the way for online use of trajectory optimization for resource-cons…
math.OC2023
Improving Computational Efficiency for Powered Descent Guidance via Transformer-based Tight Constraint Prediction
Julia Briden, Trey Gurga, Breanna Johnson +2
In this work, we present Transformer-based Powered Descent Guidance (T-PDG), a scalable algorithm for reducing the computational complexity of the direct optimization formulation o…